a permutation lempel-ziv complexity measure for eeg analysis论文.pdfVIP

Biomedical Signal Processing and Control 19 (2015) 102–114 Contents lists available at ScienceDirect Biomedical Signal Processing and Control j o u r n a l h o m ep a g e: w w w. elsev /locate/bspc A permutation Lempel-Ziv complexity measure for EEG analysis Yang Bai, Zhenhu Liang, Xiaoli Li ∗ Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China a r t i c l e i n f o a b s t r a c t Article history: Objective: In this study we develop a new complexity measure of time series by combining ordinal patterns Received 6 November 2014 and Lempel-Ziv complexity (LZC) for quantifying the dynamical changes of EEG. Received in revised form 31 March 2015 Methods: A neural mass model (NMM) was used to simulate EEG data and test the performance of the Accepted 2 April 2015 permutation Lempel-Ziv complexity (PLZC) in tracking the dynamical changes of signals against different Available online 18 April 2015 white noise levels. Then, the PLZC was applied to real EEG data to investigate whether it was able to detect the different states of anesthesia and epileptic seizures. The Z-score model, two-way ANOVA and t-test Keywords: were used to estimate the significance of the results. Electroencephalography Results: PLZC could successfully track the dynamical changes of EEG series generated by the NMM. Com- Permutation Lempel-Ziv complexity